On the Consideration of AI Openness: Can Good Intent Be Abused?
| Autor: | Kim, Yeeun, Choi, Eunkyung, Kim, Hyunjun, Oh, Hongseok, Shin, Hyunseo, Hwang, Wonseok |
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| Rok vydání: | 2024 |
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| Druh dokumentu: | Working Paper |
| Popis: | Openness is critical for the advancement of science. In particular, recent rapid progress in AI has been made possible only by various open-source models, datasets, and libraries. However, this openness also means that technologies can be freely used for socially harmful purposes. Can open-source models or datasets be used for malicious purposes? If so, how easy is it to adapt technology for such goals? Here, we conduct a case study in the legal domain, a realm where individual decisions can have profound social consequences. To this end, we build EVE, a dataset consisting of 200 examples of questions and corresponding answers about criminal activities based on 200 Korean precedents. We found that a widely accepted open-source LLM, which initially refuses to answer unethical questions, can be easily tuned with EVE to provide unethical and informative answers about criminal activities. This implies that although open-source technologies contribute to scientific progress, some care must be taken to mitigate possible malicious use cases. Warning: This paper contains contents that some may find unethical. Comment: 10 pages |
| Databáze: | arXiv |
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